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 "cells": [
  {
   "cell_type": "markdown",
   "id": "1edb9e6b",
   "metadata": {},
   "source": [
    "# ChatGPT plugin\n",
    "\n",
    ">[OpenAI plugins](https://platform.openai.com/docs/plugins/introduction) connect `ChatGPT` to third-party applications. These plugins enable `ChatGPT` to interact with APIs defined by developers, enhancing `ChatGPT's` capabilities and allowing it to perform a wide range of actions.\n",
    "\n",
    ">Plugins allow `ChatGPT` to do things like:\n",
    ">- Retrieve real-time information; e.g., sports scores, stock prices, the latest news, etc.\n",
    ">- Retrieve knowledge-base information; e.g., company docs, personal notes, etc.\n",
    ">- Perform actions on behalf of the user; e.g., booking a flight, ordering food, etc.\n",
    "\n",
    "This notebook shows how to use the ChatGPT Retriever Plugin within LangChain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bbe89ca0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# STEP 1: Load\n",
    "\n",
    "# Load documents using LangChain's DocumentLoaders\n",
    "# This is from https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html\n",
    "\n",
    "from langchain_community.document_loaders import CSVLoader\n",
    "from langchain_core.documents import Document\n",
    "\n",
    "loader = CSVLoader(\n",
    "    file_path=\"../../document_loaders/examples/example_data/mlb_teams_2012.csv\"\n",
    ")\n",
    "data = loader.load()\n",
    "\n",
    "\n",
    "# STEP 2: Convert\n",
    "\n",
    "# Convert Document to format expected by https://github.com/openai/chatgpt-retrieval-plugin\n",
    "import json\n",
    "from typing import List\n",
    "\n",
    "\n",
    "def write_json(path: str, documents: List[Document]) -> None:\n",
    "    results = [{\"text\": doc.page_content} for doc in documents]\n",
    "    with open(path, \"w\") as f:\n",
    "        json.dump(results, f, indent=2)\n",
    "\n",
    "\n",
    "write_json(\"foo.json\", data)\n",
    "\n",
    "# STEP 3: Use\n",
    "\n",
    "# Ingest this as you would any other json file in https://github.com/openai/chatgpt-retrieval-plugin/tree/main/scripts/process_json"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0474661d",
   "metadata": {},
   "source": [
    "## Using the ChatGPT Retriever Plugin\n",
    "\n",
    "Okay, so we've created the ChatGPT Retriever Plugin, but how do we actually use it?\n",
    "\n",
    "The below code walks through how to do that."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb27da9f-d574-425d-8fab-92b03b997568",
   "metadata": {},
   "source": [
    "We want to use `ChatGPTPluginRetriever` so we have to get the OpenAI API Key."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b5d8c9e9-839f-42e9-933a-08195797dd4c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "OpenAI API Key: ········\n"
     ]
    }
   ],
   "source": [
    "import getpass\n",
    "import os\n",
    "\n",
    "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "39d6074e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from langchain_community.retrievers import (\n",
    "    ChatGPTPluginRetriever,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "33fd23d1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "retriever = ChatGPTPluginRetriever(url=\"http://0.0.0.0:8000\", bearer_token=\"foo\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "16250bdf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Document(page_content=\"This is Alice's phone number: 123-456-7890\", lookup_str='', metadata={'id': '456_0', 'metadata': {'source': 'email', 'source_id': '567', 'url': None, 'created_at': '1609592400.0', 'author': 'Alice', 'document_id': '456'}, 'embedding': None, 'score': 0.925571561}, lookup_index=0),\n",
       " Document(page_content='This is a document about something', lookup_str='', metadata={'id': '123_0', 'metadata': {'source': 'file', 'source_id': 'https://example.com/doc1', 'url': 'https://example.com/doc1', 'created_at': '1609502400.0', 'author': 'Alice', 'document_id': '123'}, 'embedding': None, 'score': 0.6987589}, lookup_index=0),\n",
       " Document(page_content='Team: Angels \"Payroll (millions)\": 154.49 \"Wins\": 89', lookup_str='', metadata={'id': '59c2c0c1-ae3f-4272-a1da-f44a723ea631_0', 'metadata': {'source': None, 'source_id': None, 'url': None, 'created_at': None, 'author': None, 'document_id': '59c2c0c1-ae3f-4272-a1da-f44a723ea631'}, 'embedding': None, 'score': 0.697888613}, lookup_index=0)]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retriever.invoke(\"alice's phone number\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8b5794b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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